查看文章

This study investigated the effects of prior assumptions in applications of full Bayes methods in road safety analysis. The effect of prior choice was evaluated in the accuracy of model parameters, hotspot identification, goodness of fit, and a treatment effectiveness index in before–after studies. Particular attention was devoted to conditions with a lack of data, which were referenced as the low-mean and small-sample problem. In this research, informative, semi-informative, and noninformative priors were determined on the basis of past published studies. A simulation framework was used to evaluate various scenarios of sample size and crash occurrence mean. Quasi-simulated data were generated on the basis of two empirical databases of divided and undivided rural highway segments in New York and Texas. Various sample mean values were obtained on the basis of time period (number of years) and classifying …